Most people play Quake with a computer mouse, but researchers in David Tank’s lab at Princeton have done it with a living mouse, AND they are recording the intracellular activity of individual neurons of the mouse during the gaming session. As reported in Intracellular dynamics of hippocampal place cells during virtual navigation, the virtual reality environment of the video game was sufficiently realistic to generate place cell activity in the mouse’s hippocampus.

Now where did I see that cheese power-up?

Place cells modulate their activity dependent on the location the mouse is at. They have mostly been identified with extracellular recordings in freely moving mice. Extracellular recording only permits the detection of the rates of action potential firing, rather then the subtle intracellular voltage changes that could help explain the mechanism of place cell activity generation. A few pioneers, such as Albert “my greatest strength is a tremendous capacity for boredom” Lee, have recorded intracellularly in freely moving animals, but these experiments are fiendishly difficult, as the motion of the animal’s head tends to break the seal on the recorded neuron. Only a few cells have been recorded in that manner for more than a few minutes, though the success rate has been improving recently.

Experimental setup

In Chris Harvey’s technique, they fix the head of the mouse to a bar and let the mouse walk on a floating ball, while a virtual reality screen is projected in the mouse’s field of view. The motion of the ball controls the motion on the screen. The head never moves, so intracellular recordings can be made relatively easily and held for long periods of time.

The authors find three characteristics of place cell activity that could explain their generation and function.

“An asymmetric ramp-like depolarization of the baseline membrane potential, an increase in the amplitude of intracellular theta oscillations, and a phase precession of the intracellular theta oscillation relative to the extracellularly recorded theta rhythm.”

Intracellular voltage dynamics in place cells

These could be used to explain how place cells remap their selectivity when a mouse (or a human) moves into a new environment. This also could be used to do more in depth studies of the mental replay of place locations that has been previously recorded in the activity patterns of the hippocampus. The technique itself is about as sexy as neuroscience gets. Unfortunately, this paper also provides an additional piece of evidence for Karel to use in motivating lab post-docs, “Look at Chris, he left the lab after you got here and already has a Nature article…”‘

Every week or two one of the post-doc’s in our lab passes around a paper that is as much philosophy of science as experimental result. One that recently made the rounds is Can a Biologist Fix a Radio?, by Yuri Lazebnik, a spirited and humorous dissection of the flaws of the standard methods of experimentation and analysis in cell and systems biology. The primary contention is that most biologists are not sufficiently quantitative in their descriptions of the interactions of components in their system, which leads to an abundance of confusing, conflicting experimental results. If we hope to understand complex biological systems, we must describe the components in sufficient detail, with a standardized language, to allow accurate models built from numerous components. A radio can be perfectly described by its circuit diagram due to the quantitative knowledge of the component properties. Using a simplistic biological pathway diagram provides little insight.

Two schematics of a radio. The biologist's view (top), and the engineer's view (bottom).

Recently, a similar paper, On the Precarious Path of Reverse Neuro-Engineering, in Frontiers in Computations Neuroscience, highlighted a logical flaw in how much neuroscience research is done. When we find patterns or correlations between an external signal to neuronal activity, the tendency is to proclaim “Aha! This is how the circuit represents information and what it uses to make decisions.” But correlation does not equal causation. In this paper the authors build a physical Braitenberg Vehicle II, which is a component of a classic thought experiment in neuroscience. It navigates an environment by acquiring optical input, processing it through a network of cultured neurons, and then controlling a motor output through a simple rule about the firing of the neurons. Recording the activity of the neurons leads to the discovery of a ‘population rate code’ in the activity of the neurons, which describes the behavior of the robot fairly accurately. An experimental biologist would be tempted to call this finding the ‘neural code’ of the system. But, the navigation rule that robot actually follows is not based spike rates at all, but rather the order of first spikes in a handful of the neurons in the network. The correlation between population rate activity and behavior is real, but it is not what is relevant to the circuit and the behavior. This example cuts deep, and hits my unease with much current brain circuit analysis. There are huge numbers of papers that show particular stimulus features can be extracted from the firing patterns of neurons in a particular brain region, but rarely does a study conclusively demonstrate that the circuit actually uses these correlations in the computational task. Demonstrating causality is difficult, but essential if we are to gain an understanding of how brain circuits really work.

Despite the presence of many spikes (blue) and a population spike rate, the robot only cares about the delay to time of the first spike (black circle) in a subset of neurons.

It’s the data that Graduate Schools and US News & World Report doesn’t want you to know. For the last several years Wendy Chao has compiled a list of stipends at various graduate biomedical research programs around the country. Who pays the most in real and cost of living adjusted terms? Find out at America’s Best Graduate School Stipends. If you’ve got a salary to report, let her know!

I’m so happy now that I’m rolling in the dough as a post-doc, I don’t have to worry about stuff like this. 😉

For technically demanding protocols in neuroscience (or any other science) research, a printed protocol is often insufficient to capture all the essentials of a method. There are usually numerous ‘tricks’ or things that one must pay attention to that are not included in the printed page. Or, if they are included, they still lack a vivid description. Many techniques require the novice to be taught the technique from a more experienced colleage. Unfortunately, it is not always easy to find someone skilled to be trained from. Labs which pioneer the techniques have only a limited amount of time and resources available to train outside scientists. How can advanced scientific skills be distributed more broadly and efficiently? A good place to start is the Journal of Visualized Experiments (JoVE). It’s a YouTube for science protocols.

So that's how you do it!

JoVE is a growing collection of video protocols that walk a researcher through the procedure, allowing one to actually see the steps used, rather than just imaging what performing the protocol might be like. Want to know how to glue a live fruit fly to a stick? Just watch the video! Wonder how to load calcium dyes onto the cortex of a mouse? Just watch the video! This looks to be a fantastic resource for people that are learning a technique, that want to see other possible ways to do a procedure, or those who are simply curious about what a neuroscientist actually does at work.

Did you know that a geodesic sphere is so light that if one were constructed with a half-mile diameter, raising the temperature inside by a single degree cause it to float away like a soap bubble? It’s a stretch to say this post is brain imaging related… But perhaps there is something useful in learning about maximally efficient constructible structures.

Geodesic Math...

Spent a few weeks this fall building a geodesic dome. 5/8 height, 3 frequency dome. 24′ radius, 15′ height. Took about 20 long hours to fabricate (thank you Janelia Remote Machine Shop), 3 hours to assemble, 1 to take down. Strung a strong net across the 8 foot level for bouncing around on. Plans and calculators are online. I’ve only used it once, as a beta test, and I’m already itching for something more complex. Luckily I just got the book Geodesic Math and How to Use It off Amazon. It’s a great theoretical and practical guide to the design of geodesic structures. Not just domes, but eggs and freeform contours. It was the most requested back-catalog book in Univ. of California’s publishing history. It has just been reprinted. You can get a copy here. Giant blinking 3D geodesic brain… I can see it now…